IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p10149-d1525487.html
   My bibliography  Save this article

An Empirical Analysis of the Characteristics and Determinants of the China–ASEAN Science and Technology Cooperation Network: Insights from Co-Authored Publications

Author

Listed:
  • Fan Wu

    (School of Public Policy and Management, Guangxi University, Nanning 530004, China)

  • Zhixu Liu

    (School of Public Policy and Management, Guangxi University, Nanning 530004, China)

Abstract

Regional science and technology cooperation networks are pivotal for fostering sustainable global innovation. The China–ASEAN science and technology cooperation network integrates regional innovation resources, thereby promoting the sustainable flow of innovation elements and complementing technological strengths among countries, which significantly enhances cooperation efficiency and outcomes. This study employs a Social Network Analysis (SNA) and the Temporal Exponential Random Graph Model (TERGM) to analyze co-authored publications between China and ASEAN countries from 2003 to 2022, constructing a cooperation network that integrates both endogenous network structures and exogenous driving factors. This study explores the distinct mechanisms through which these factors influence the formation of cooperative relationships and highlights the key features and determinants of the network. The findings reveal the following: first, the China–ASEAN science and technology cooperation network has evolved from an initial “star-shaped structure” with China and Singapore as central nodes to a more interconnected network exhibiting “small world” and “high clustering” characteristics. Second, endogenous network structures, including the number of edges, node centrality, and closed triadic structures, significantly shape the network’s evolution, with some structures inhibiting the formation of new partnerships, while an increase in shared collaborators promotes new connections. Third, the evolution of the network demonstrates both stability and variability. Fourth, human capital is a key driver of partnership formation, while higher per-capita GDP countries show less inclination to form new partnerships. Fifth, proximity factors have heterogeneous effects: linguistic proximity positively impacts the formation of partnerships, while institutional proximity negatively affects the establishment of new collaborations. Based on these findings, this paper suggests improving international cooperation mechanisms, optimizing resource allocation, and enhancing the development of cross-border scientific talent. These measures aim to enhance the connectivity within the China–ASEAN science and technology cooperation network, effectively improve the utilization efficiency of regional innovation resources and technological capabilities, and promote the sharing and long-term collaboration of innovation resources within the region, thereby advancing sustainable development at both regional and global levels.

Suggested Citation

  • Fan Wu & Zhixu Liu, 2024. "An Empirical Analysis of the Characteristics and Determinants of the China–ASEAN Science and Technology Cooperation Network: Insights from Co-Authored Publications," Sustainability, MDPI, vol. 16(22), pages 1-24, November.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:10149-:d:1525487
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/10149/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/22/10149/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jarno Hoekman & Koen Frenken & Frank Oort, 2009. "The geography of collaborative knowledge production in Europe," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(3), pages 721-738, September.
    2. Ali Gazni & Cassidy R. Sugimoto & Fereshteh Didegah, 2012. "Mapping world scientific collaboration: Authors, institutions, and countries," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(2), pages 323-335, February.
    3. Ali Gazni & Cassidy R. Sugimoto & Fereshteh Didegah, 2012. "Mapping world scientific collaboration: Authors, institutions, and countries," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 323-335, February.
    4. Steven Goodreau & James Kitts & Martina Morris, 2009. "Birds of a feather, or friend of a friend? using exponential random graph models to investigate adolescent social networks," Demography, Springer;Population Association of America (PAA), vol. 46(1), pages 103-125, February.
    5. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. Fernández & E. Ferrándiz & M. D. León, 2016. "Proximity dimensions and scientific collaboration among academic institutions in Europe: The closer, the better?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1073-1092, March.
    2. Cathelijn J F Waaijer & Benoît Macaluso & Cassidy R Sugimoto & Vincent Larivière, 2016. "Stability and Longevity in the Publication Careers of U.S. Doctorate Recipients," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-15, April.
    3. Seokbeom Kwon & Jan Youtie & Alan Porter & Nils Newman, 2024. "How does regulatory uncertainty shape the innovation process? Evidence from the case of nanomedicine," The Journal of Technology Transfer, Springer, vol. 49(1), pages 262-302, February.
    4. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    5. Wencan Tian & Ruonan Cai & Zhichao Fang & Yu Geng & Xianwen Wang & Zhigang Hu, 2024. "Understanding co‐corresponding authorship: A bibliometric analysis and detailed overview," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(1), pages 3-23, January.
    6. Tang, Kun & Li, Baiyang & Zhu, Qiyu & Ma, Lecun, 2024. "Disruptive content, cross agglomeration interaction, and agglomeration replacement: Does cohesion foster strength?," Journal of Informetrics, Elsevier, vol. 18(4).
    7. Xinzhe Li & Xiao Lu, 2025. "Analysis of the research collaboration organizational characteristics and scientific impact of large-scale research facilities: a case study of Chinese large-scale research facilities," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(5), pages 2639-2671, May.
    8. Chaocheng He & Jiang Wu & Qingpeng Zhang, 2021. "Characterizing research leadership on geographically weighted collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4005-4037, May.
    9. Ba Xuan Nguyen & Markus Luczak-Roesch & Jesse David Dinneen, 2024. "Do research collaborations age like wine? Absolute and relative measures of CANZUK research partnerships’ strength since the 1950s," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-24, April.
    10. A. Velez-Estevez & P. García-Sánchez & J. A. Moral-Munoz & M. J. Cobo, 2022. "Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7517-7555, December.
    11. Louise C. O'Keefe & Karen H. Frith & Elizabeth Barnby, 2017. "Nurse faculty as international research collaborators," Nursing & Health Sciences, John Wiley & Sons, vol. 19(1), pages 119-125, March.
    12. Ali Sina Önder & Sascha Schweitzer & Hakan Yilmazkuday, 2021. "Field Distance and Quality in Economists’ Collaborations," Working Papers in Economics & Finance 2021-04, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    13. Jesús Frutos-Belizón & Natalia García-Carbonell & Félix Guerrero-Alba & Gonzalo Sánchez-Gardey, 2024. "An empirical analysis of individual and collective determinants of international research collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(5), pages 2749-2770, May.
    14. Nina Liu & Jiwu Wang & Yan Song, 2019. "Organization Mechanisms and Spatial Characteristics of Urban Collaborative Innovation Networks: A Case Study in Hangzhou, China," Sustainability, MDPI, vol. 11(21), pages 1-18, October.
    15. Ekaterina Dyachenko & Iurii Agafonov & Katerina Guba & Alexander Gelvikh, 2024. "Independent Russian medical science: is there any?," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5577-5597, September.
    16. JongWuk Ahn & Hyundo Choi & Dong-hyun Oh, 2019. "Leveraging bridging universities to access international knowledge: Korean universities’ R&D internationalization," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 519-537, August.
    17. Ali Gazni & Vincent Larivière & Fereshteh Didegah, 2016. "The effect of collaborators on institutions’ scientific impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1209-1230, November.
    18. Lipeng Fan & Yuefen Wang & Shengchun Ding & Binbin Qi, 2020. "Productivity trends and citation impact of different institutional collaboration patterns at the research units’ level," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1179-1196, November.
    19. Ruonan Cai & Wencan Tian & Rundong Luo & Zhigang Hu, 2024. "The generation mechanism of research leadership in international collaboration based on GERGM: a case from the field of artificial intelligence," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(10), pages 5821-5839, October.
    20. Didegah, Fereshteh & Thelwall, Mike, 2013. "Which factors help authors produce the highest impact research? Collaboration, journal and document properties," Journal of Informetrics, Elsevier, vol. 7(4), pages 861-873.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:10149-:d:1525487. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.